Optical Character Recognition software (OCR) are important tools for obtaining accessible texts. We propose the use of artificial neural networks (ANN) in order to develop pattern recognition algorithms capable of recognizing both normal texts and formulae. We present an original improvement of the backpropagation algorithm. Moreover, we describe a novel image segmentation algorithm that exploits fuzzy logic for separating touching characters.

Artificial Neural Networks and Fuzzy Logic for Recognizing Alphabet Characters and Mathematical Symbols / AIRO' FARULLA, Giuseppe; Armano, Tiziana; Capietto, Anna; Murru, Nadir; Rossini, Rosaria. - ELETTRONICO. - 9758:(2016), pp. 7-14. ((Intervento presentato al convegno Computers Helping People with Special Needs, 15th International Conference, ICCHP 2016 tenutosi a Linz (AUSTRIA) nel July 13-15, 2016 [10.1007/978-3-319-41264-1_1].

Artificial Neural Networks and Fuzzy Logic for Recognizing Alphabet Characters and Mathematical Symbols

AIRO' FARULLA, GIUSEPPE;MURRU, NADIR;
2016

Abstract

Optical Character Recognition software (OCR) are important tools for obtaining accessible texts. We propose the use of artificial neural networks (ANN) in order to develop pattern recognition algorithms capable of recognizing both normal texts and formulae. We present an original improvement of the backpropagation algorithm. Moreover, we describe a novel image segmentation algorithm that exploits fuzzy logic for separating touching characters.
978-3-319-41263-4
978-3-319-41264-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2644850
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